639 resultados para ISSN-tunnus
Resumo:
Mg alloys can be used as bioresorsable metallic implants. However, the high corrosion rate of magnesium alloys has limited their biomedical applications. Although Mg ions are essential to the human body, an excess may cause undesirable health effects. Therefore, surface treatments are required to enhance the corrosion resistance of magnesium parts, decreasing its rate to biocompatible levels and allowing its safe application as bioresorbable metallic implants. The application of biocompatible silane coatings is envisaged as a suitable strategy for retarding the corrosion process of magnesium alloys. In the current work, a new glycidoxypropyltrimethoxysilane (GPTMS) based coating was tested on AZ31 magnesium substrates subjected to different surface conditioning procedures before coating deposition. The surface conditioning included a short etching with hydrofluoric acid (HF) or a dc polarisation in alkaline electrolyte. The silane coated samples were immersed in Hank's solution and the protective performance of the coating was studied through electrochemical impedance spectroscopy (EIS). The EIS data was treated by new equivalent circuit models and the results revealed that the surface conditioning process plays a key role in the effectiveness of the silane coating. The HF treated samples led to the highest impedance values and delayed the coating degradation, compared to the mechanically polished samples or to those submitted to dc polarisation.
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When considering time series data of variables describing agent interactions in social neurobiological systems, measures of regularity can provide a global understanding of such system behaviors. Approximate entropy (ApEn) was introduced as a nonlinear measure to assess the complexity of a system behavior by quantifying the regularity of the generated time series. However, ApEn is not reliable when assessing and comparing the regularity of data series with short or inconsistent lengths, which often occur in studies of social neurobiological systems, particularly in dyadic human movement systems. Here, the authors present two normalized, nonmodified measures of regularity derived from the original ApEn, which are less dependent on time series length. The validity of the suggested measures was tested in well-established series (random and sine) prior to their empirical application, describing the dyadic behavior of athletes in team games. The authors consider one of the ApEn normalized measures to generate the 95th percentile envelopes that can be used to test whether a particular social neurobiological system is highly complex (i.e., generates highly unpredictable time series). Results demonstrated that suggested measures may be considered as valid instruments for measuring and comparing complexity in systems that produce time series with inconsistent lengths.
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Co-deposition of nickel and cobalt was carried out on austenitic stainless steel (AISI 304) substrates by imposing a square waveform current in the cathodic region. The innovative procedure applied in this work allows creating a stable, fully developed, and open porous three-dimensional (3D) dendritic structure, which can be used as electrode for redox supercapacitors. This study investigates in detail the influence of the applied current density on the morphology, mass, and chemical composition of the deposited Ni-Co films and the resulting 3D porous network dendritic structure. The morphology and the physicochemical composition were studied by scanning electron microscopy (SEM), energy dispersive X-ray spectroscopy (EDS) and X-ray diffraction (W). The electrochemical behavior of the materials was evaluated by cyclic voltammetry (CV). The results highlight the mechanism involved in the coelectrodeposition process and how the lower limit current density tailors the film composition and morphology, as well as its electrochemical activity.
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In the field of appearance-based robot localization, the mainstream approach uses a quantized representation of local image features. An alternative strategy is the exploitation of raw feature descriptors, thus avoiding approximations due to quantization. In this work, the quantized and non-quantized representations are compared with respect to their discriminativity, in the context of the robot global localization problem. Having demonstrated the advantages of the non-quantized representation, the paper proposes mechanisms to reduce the computational burden this approach would carry, when applied in its simplest form. This reduction is achieved through a hierarchical strategy which gradually discards candidate locations and by exploring two simplifying assumptions about the training data. The potential of the non-quantized representation is exploited by resorting to the entropy-discriminativity relation. The idea behind this approach is that the non-quantized representation facilitates the assessment of the distinctiveness of features, through the entropy measure. Building on this finding, the robustness of the localization system is enhanced by modulating the importance of features according to the entropy measure. Experimental results support the effectiveness of this approach, as well as the validity of the proposed computation reduction methods.
Resumo:
An aneurysm is a localized blood-filled dilatation of an artery whose consequences can be deadly. One of its current treatments is endovascular aneurysm repair, a minimally invasive procedure in which an endoprosthesis, called a stent-graft, is placed transluminally to prevent wall rupture. Early stent-grafts were custom designed for the patient through the assembling of off-the-shelf components by the operating surgeon. However, nowadays, stent-grafts have become a commercial product. The existing endoprostheses differ in several aspects, such as shape design and materials, but they have in common a metallic scaffold with a polymeric covering membrane. This article aims to gather relevant information for those who wish to understand the principles of stent-grafts and even to develop new devices. Hence, a stent-graft classification based on different characteristics is presented and the desired features for an ideal device are pointed out. Additionally, the materials currently in use to fabricate this type of endoprosthesis are reviewed and new materials are suggested.
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Team sports represent complex systems: players interact continuously during a game, and exhibit intricate patterns of interaction, which can be identified and investigated at both individual and collective levels. We used Voronoi diagrams to identify and investigate the spatial dynamics of players' behavior in Futsal. Using this tool, we examined 19 plays of a sub-phase of a Futsal game played in a reduced area (20 m(2)) from which we extracted the trajectories of all players. Results obtained from a comparative analysis of player's Voronoi area (dominant region) and nearest teammate distance revealed different patterns of interaction between attackers and defenders, both at the level of individual players and teams. We found that, compared to defenders, larger dominant regions were associated with attackers. Furthermore, these regions were more variable in size among players from the same team but, at the player level, the attackers' dominant regions were more regular than those associated with each of the defenders. These findings support a formal description of the dynamic spatial interaction of the players, at least during the particular sub-phase of Futsal investigated. The adopted approach may be extended to other team behaviors where the actions taken at any instant in time by each of the involved agents are associated with the space they occupy at that particular time.
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A design methodology for monolithic integration of inductor based DC-DC converters is proposed in this paper. A power loss model of the power stage, including the drive circuits, is defined in order to optimize efficiency. Based on this model and taking as reference a 0.35 mu m CMOS process, a buck converter was designed and fabricated. For a given set of operating conditions the defined power loss model allows to optimize the design parameters for the power stage, including the gate-driver tapering factor and the width of the power MOSFETs. Experimental results obtained from a buck converter at 100 MHz switching frequency are presented to validate the proposed methodology.
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This paper provides a review of antennas applied for indoor positioning or localization systems. The desired requirements of those antennas when integrated in anchor nodes (reference nodes) are discussed, according to different localization techniques and their performance. The described antennas will be subdivided into the following sections according to the nature of measurements: received signal strength (RSS), time of flight (ToF), and direction of arrival (DoA). This paper intends to provide a useful guide for antenna designers who are interested in developing suitable antennas for indoor localization systems.
Resumo:
Many learning problems require handling high dimensional datasets with a relatively small number of instances. Learning algorithms are thus confronted with the curse of dimensionality, and need to address it in order to be effective. Examples of these types of data include the bag-of-words representation in text classification problems and gene expression data for tumor detection/classification. Usually, among the high number of features characterizing the instances, many may be irrelevant (or even detrimental) for the learning tasks. It is thus clear that there is a need for adequate techniques for feature representation, reduction, and selection, to improve both the classification accuracy and the memory requirements. In this paper, we propose combined unsupervised feature discretization and feature selection techniques, suitable for medium and high-dimensional datasets. The experimental results on several standard datasets, with both sparse and dense features, show the efficiency of the proposed techniques as well as improvements over previous related techniques.
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This paper proposes a possible implementation of a compact printed monopole antenna, useful to operate in UMTS and WLAN bands. In order to accomplish that, a miniaturization technique based on the application of chip inductors is used in conjunction with frequency reconfiguration capability. The chip inductors change the impedance response of the monopole, allowing to reduce the resonant frequency. In order to be able to operate the antenna in these two different frequencies, an antenna reconfiguration technique based on PIN diodes is applied. This procedure allows the change of the active form of the antenna leading to a shift in the resonant frequency. The prototype measurements show good agreement with the simulation results.
Resumo:
In this paper we present results about the functioning of a multilayered a-SiC:H heterostructure as a device for wavelength-division demultiplexing of optical signals. The device is composed of two stacked p-i-n photodiodes, both optimized for the selective collection of photogenerated carriers. Band gap engineering was used to adjust the photogeneration and recombination rates profiles of the intrinsic absorber regions of each photodiode to short and long wavelength absorption and carrier collection in the visible spectrum. The photocurrent signal using different input optical channels was analyzed at reverse and forward bias and under steady state illumination. This photocurrent is used as an input for a demux algorithm based on the voltage controlled sensitivity of the device. The device functioning is explained with results obtained by numerical simulation of the device, which permit an insight to the internal electric configuration of the double heterojunction.These results address the explanation of the device functioning in the frequency domain to a wavelength tunable photocapacitance due to the accumulation of space charge localized at the internal junction. The existence of a direct relation between the experimentally observed capacitive effects of the double diode and the quality of the semiconductor materials used to form the internal junction is highlighted.
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Feature selection is a central problem in machine learning and pattern recognition. On large datasets (in terms of dimension and/or number of instances), using search-based or wrapper techniques can be cornputationally prohibitive. Moreover, many filter methods based on relevance/redundancy assessment also take a prohibitively long time on high-dimensional. datasets. In this paper, we propose efficient unsupervised and supervised feature selection/ranking filters for high-dimensional datasets. These methods use low-complexity relevance and redundancy criteria, applicable to supervised, semi-supervised, and unsupervised learning, being able to act as pre-processors for computationally intensive methods to focus their attention on smaller subsets of promising features. The experimental results, with up to 10(5) features, show the time efficiency of our methods, with lower generalization error than state-of-the-art techniques, while being dramatically simpler and faster.
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We report and analyze the halting of the fuse effect propagation in optical fiber microwires. The increase of the mode field diameter in the tapered region decreases the optical intensity resulting in the extinction of the fuse effect. This fiber element presents a low insertion loss and can be introduced in the optical network in order to protect the active equipment from the damage caused by the fuse effect.
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This paper introduces a new unsupervised hyperspectral unmixing method conceived to linear but highly mixed hyperspectral data sets, in which the simplex of minimum volume, usually estimated by the purely geometrically based algorithms, is far way from the true simplex associated with the endmembers. The proposed method, an extension of our previous studies, resorts to the statistical framework. The abundance fraction prior is a mixture of Dirichlet densities, thus automatically enforcing the constraints on the abundance fractions imposed by the acquisition process, namely, nonnegativity and sum-to-one. A cyclic minimization algorithm is developed where the following are observed: 1) The number of Dirichlet modes is inferred based on the minimum description length principle; 2) a generalized expectation maximization algorithm is derived to infer the model parameters; and 3) a sequence of augmented Lagrangian-based optimizations is used to compute the signatures of the endmembers. Experiments on simulated and real data are presented to show the effectiveness of the proposed algorithm in unmixing problems beyond the reach of the geometrically based state-of-the-art competitors.
Resumo:
Characteristics of tunable wavelength pi'n/pin filters based on a-SiC:H multilayered stacked cells are studied both experimentally and theoretically. Results show that the device combines the demultiplexing operation with the simultaneous photodetection and self amplification of the signal. An algorithm to decode the multiplex signal is established. A capacitive active band-pass filter model is presented and supported by an electrical simulation of the state variable filter circuit. Experimental and simulated results show that the device acts as a state variable filter. It combines the properties of active high-pass and low-pass filter sections into a capacitive active band-pass filter using a changing capacitance to control the power delivered to the load.